Convergence of trading strategies in continuous double auction markets with boundedly-rational networked traders

This paper considers the convergence of trading strategies among artificial traders connected to one another in a social network and trading in a continuous double auction financial marketplace. Convergence is studied by means of an agent-based simulation model called the Social Network Artificial stoCk marKet model. Six different canonical network topologies (including no-network) are used to represent the possible connections between artificial traders. Traders learn from the trading experiences of their connected neighbours by means of reinforcement learning. The results show that the proportions of traders using particular trading strategies are eventually stable. Which strategies dominate in these stable states depends to some extent on the particular network topology of trader connections and the types of traders.     

Preferred suppliers in auction markets

This article examines agreements between a buyer and one of the suppliers which increase their joint surplus. The provisions of such agreements depend on the buyer's ability to design the rules of the final procurement auction. When the buyer does not have this ability, their joint surplus can be increased by an agreement which grants to the preferred supplier a right of first refusal on the lowest price from the other suppliers. When the buyer has this ability, their joint surplus can be maximized by a revelation game for the cost of the preferred supplier and a reserve price based on that cost.     

Integrating auction and search markets: The slow Dutch auction

The issue of choosing to sell property by auction or by traditional negotiated search markets is addressed in this article. A general selling institution called the slow Dutch auction is introduced. This general selling mechanism reduces to either a conventional auction, a posted offer, or some time dependent mix of these selling institutions depending on the pricing rule chosen by the seller. We model search by having potential buyers whose private valuation for the property is unknown to the seller arrive randomly over time. With this general framework the seller's problem is to choose a selling mechanism that maximizes expected wealth. Surprisingly, we find that the optimal selling institution is always a posted offer market. The seller chooses an optimal posted price and waits until a buyer arrives who is willing to pay this price. Auctions are never optimal.     

Volatility,information, and double versus walrasian auction pricing in US and Japanese futures markets

This study empirically examines volatility in US and Japanese commodity futures markets. The US futures market, COMEX, is double auction with continuous trading, whereas the Japanese futures market, TOCOM, was Walrasian with discrete trading until April 1991. We find intraday volatility for gold futures contracts to be significantly higher on COMEX than TOCOM throughout the sample period and is attributable to differences in information flows and market micro-structures. Evidence is also provided that exchange volume conveys information both within and across markets, which is consistent with the French and Roll, 1986 (French, K.R., Roll, R., 1986. Stock return variances: The arrival of information and the reaction of traders. Journal of Financial Economics 17, 5–26) private-information based rational trading model. Finally, daily variance and autocorrelation estimates within COMEX are consistent with the extant literature on equity markets.     

Optimal auction design in two‐sided markets

A key feature of online markets for advertising (e.g., sponsored links) is that clicking rates depend on the searchers' expectations that the platform selects relevant advertisers. This article studies auction design by a platform that maximizes profits in the long run, where clicking rates are mechanism dependent. In line with the practice of the major search engines, the revenue‐maximizing mechanism is a scoring auction that combines the willingness to pay and the relevance to searchers of advertisers. By trading off rent extraction and clicking volume, this mechanism works as a cross‐subsidization device between searchers and advertisers.     

Price discovery in auction markets: a look inside the black box

Opening mechanisms play a crucial role in information aggregationfollowing the overnight nontrading period. This article examinesthe process of price discovery at the New York Stock Exchangesingle-price opening auction. We develop a theoretical modelto explain the determinants of the opening price and test themodel using order-level data. We show that the presence of designateddealers facilitates price discovery relative to a fully automatedcall auction market. This is consistent with specialists extractinginformation from observing the evolution of the limit orderbook. In addition, the specialist's opening trade reflects noninformationalfactors such as price stabilization requirements.     

Insider trading in sequential auction markets with risk-aversion and time-discounting

We extend Kyle's [Kyle, A. S. 1985. “Continuous Auctions and Insider Trading.” Econometrica 53, 1315–1335] analysis of sequential auction markets to the case in which the insider is risk-averse and discounts her trading profits as her private information is long-lived. We see that time-discounting exacerbates the impact of risk-aversion on the optimal trading strategy of the insider. Ceteris paribus, a larger degree of risk-aversion or a smaller time-discount factor induces the informed agent to consume more rapidly her informational advantage increasing the liquidity and efficiency of the securities market.     

The microstructure of Asian equity markets

This study provides an overview of six stock markets in Asia, including Hong Kong, Korea, Malaysia, Singapore, Taiwan, and Thailand. We find that the Asian stock exchanges have adopted numerous new concepts in terms of market structure, trading method, and the clearing and settlement system. As a group, they provide an intersting setting for empirical investigation due to their unique characteristics not found in the stock exchanges in advanced countries.     

A simulation analysis of the microstructure of an order driven financial market with multiple securities and portfolio choices

In this paper we propose an artificial market where multiple risky assets are exchanged. Agents are constrained by the availability of resources and trade to adjust their portfolio according to an exogenously given target portfolio. We model the trading mechanism as a continuous auction order-driven market. Agents are heterogeneous in terms of desired target portfolio allocations, but they are homogeneous in terms of trading strategies. We investigate the role played by the trading mechanism in affecting the dynamics of prices, trading volume and volatility. We show that the institutional setting of a double auction market is sufficient to generate a non-normal distribution of price changes and temporal patterns that resemble those observed in real markets. Moreover, we highlight the role played by the interaction between individual wealth constraints and the market frictions associated with a double auction system to determine the negative asymmetry of the stock returns distribution.     

Market structure, informational efficiency and liquidity: An experimental comparison of auction and dealer markets

We report the results of 18 market experiments that were conducted in order to compare the call market, the continuous auction and the dealer market. Transaction prices in the call and continuous auction markets are much more efficient than prices in the dealer markets. The call market shows a tendency towards underreaction to new information. Execution costs are lowest in the call market and highest in the dealer market. The trading volume and Roll's (Journal of Finance (1984) 1127–1139) serial covariance estimator are inappropriate measures of execution costs in the present context. The relation between private signals, trading decisions and trading profits is analyzed.     

Price discovery and microstructure in ether spot and derivative markets

Ethereum is an important blockchain, being the first and most popular public platform for the smart contracts underpinning financial transactions, time-stamping of supply chains, decentralized applications and initial coin offerings. Ethereum's cryptocurrency, ether, is actively traded on centralized exchanges, second only to bitcoin. It has attracted investor's interest primarily because of its intrinsic value – small units of ether called ‘gas’ are used, essentially, as the fuel driving smart contract transactions on the Ethereum blockchain. We ask whether off-chain trading on ether derivatives plays a dominant role in ether spot price discovery, thereby driving ether's utility value for on-chain activity. Using minute-by-minute data we find that the ether perpetual swap on BitMEX, an unregulated cryptocurrency derivative exchange, has dominant trading volume and price discovery over the major spot exchanges. Furthermore, we identify interesting hour-of-day and day-of-week effects in trading volume on the spot exchanges, and these indicate that more informed institutional players are trading ether spot and derivatives.     

Integration of 22 emerging stock markets: A three-dimensional analysis

We apply the three-dimensional analysis of wavelet coherency to examine the integration of 22 emerging stock markets with the U.S. market. We find a high degree of co-movement at relatively lower frequencies between the U.S. and the 22 individual emerging markets. Our results show that the strength of co-movement, however, differs by country. For example, we report a high degree of co-movement between the U.S. and Brazil, Mexico and Korea, but low co-movement with and Egypt and Morocco. Our analyses also document a general change in the pattern of the market relationship after 2006, where we detect co-movements at relatively higher frequencies. Co-movement at the highest frequencies is, however, weak for fluctuations with duration less than a year. Our findings imply that investing selectively in emerging markets may provide significant diversification benefits which, invariably, depend on the investment horizon.     

Market structure and microstructure, in international interest rate futures markets

We examine the role of market structure in identifying microstructure features of the NYSE.Euronext-LIFFE STIR futures market by comparing the ability of two bid-ask spread component models to explain bid-ask spreads. These two models differ only in their assumptions about whether or not market makers are present. The period we analyze includes data from pit-based trading alongside electronic market data. We explore how market structure affects the way private information influences bid-ask spreads and return volatility. A second part of our study employs intraday correlation to investigate these links in greater depth, while a third part looks at how private information and trading noise contribute to price evolution.     

Comparing COVID-19 with the GFC: A shockwave analysis of currency markets

I analyze the shockwave effect of the COVID-19 pandemic on currency markets, with a comparison to the global financial crisis (GFC), employing Kapetanios m-break unit root test, investigations of standalone risk measures—downside variance, upside risk, volatility skewness, Gaussian Value at Risk (VaR), historical VaR, modified VaR—and Diebold–Yilmaz volatility spillover analysis. Standalone risk analysis shows that the turmoil in the initial months of COVID-19 was not as severe as that in the GFC. However, examination of co-movements and volatility spillovers illustrates a different scenario. According to the results of the static connectedness measure of Diebold–Yilmaz, the shockwave of the COVID-19 pandemic in the total volatility spillover is about eight times greater than that of the GFC. Among standalone risk measures, the results closest to this finding are obtained from volatility skewness analysis. Additionally, of six foreign exchange rates, the Brazilian real and Turkish lira are the currencies experiencing the greatest increase in received volatility during the GFC and the COVID-19 pandemic, respectively. These findings suggest the severe effect of crises on emerging financial markets.     

Modifying a simple agent-based model to disentangle the microstructure of Chinese and US stock markets

We modify a simple agent-based model (ABM) proposed by Franke and Westerhoff [J. Econ. Dyn. Control, 2012, 36(8), 1193–1211] through considering the price limits and the motion of the fundamental value. The method of simulated moments is applied to calibrate both initial and modified ABMs with CSI 300 and S&P 500 respectively, and the goodness-of-fit of each ABMs is tested. The calibration results indicate that the modified model performs better than initial one. Then, we utilize the GSL-div, proposed by Lamperti [Econometrics Stat, 2018, 5, 83–106.], to verify the explanatory power of ABMs. In this procedure, 13 ARCH family models are introduced as benchmarks. The result shows that the explanatory power of modified ABM exceeds ARCH models in both markets, while initial ABM may be defeated by some of the ARCH family models in explaining the microstructure of CSI 300. Finally, a heuristic algorithm is designed to disentangle the insights of Chinese and US stock markets to the observed time horizon through calibrating the initial fundamental value, and Kupiec test is used to check the robustness of the calibration. The result indicates that the explanation of modified model is robust in both markets, while initial model lost its robustness when explaining S&P 500.     

An empirical analysis of the equity markets in China

This paper subjects the newly established stock markets in Shanghai and Shenzhen to tests of market efficiency, utilizing daily stock price data. Using a battery of tests, the study concludes that there are significant inefficiencies present on both exchanges. These can be traced to the unique structural and institutional problems that plague both exchanges. The study also tests for the presence of seasonal anomalies on both exchanges. The results show that there are significant negative weekend and positive holiday effects, but there is no evidence of a January effect or early January effect.     

On the usefulness of the contrarian strategy across national stock markets: A grid bootstrap analysis

This paper statistically evaluates the usefulness of the contrarian investment strategy across the national stock markets of 18 developed countries. The contrarian strategy implicitly assumes that asset prices tend toward a fundamental value path over time. Conventional bootstrap analyses and panel unit root tests are often consistent with such a hypothesis. However, these results might be contaminated by small-sample bias and/or by not controlling cross-section dependence. Correcting for small-sample bias nonparametrically, I find extremely slow mean reversion rates, which provide strong evidence against the usefulness of the contrarian strategy.     

On the drivers of technical analysis profits in cryptocurrency markets: A Distributed Lag approach

The cryptocurrency literature on technical analysis has largely ignored drivers of technical analysis return adjusted by transaction costs (i.e., adjusted returns). To that end, we propose a Heterogeneous Autoregressive Distributed Lag Model of Returns (HARDL-R) to examine the impact from EPU, VIX, and SP500 returns to adjusted returns. We provide evidence that these three drivers matter during bubble periods compared to non-bubble periods. When not differentiating bubble periods, we find that VIX is the only driver influencing the dynamics of adjusted returns from 2016 to 2021. These findings remain relatively stable after controlling for the volume of transactions.     

An analysis of the liquidity benefits provided by secondary markets

Listing shares in liquid secondary markets either to facilitate acquisitions or to diversify owner’s personal wealth are among the most important reasons for firms to go public [Brau, J.C., Fawcett, S.E., 2006. Initial public offerings: An analysis of theory and practice. Journal of Finance 61, 399–436]. We contend that the expected benefits derived from the liquidity provided by secondary markets are relevant for understanding important decisions made in preparation for an IPO. We hypothesize that the potential losses caused by an IPO failure induce firms that benefit more from going public to hire more reputable underwriters and to adopt more conservative pricing policies. We use several proxies for the benefits firms derive from post-IPO liquidity. The results indicate that firms that benefited more from liquidity were taken public by more prestigious underwriters and exhibited substantially larger levels of price revisions and underpricing. Post-IPO liquidity is also important for understanding the decision to retain the lead underwriter in subsequent SEOs.